// How-to · Private LLMs and knowledge bases for the enterprise
Employees paste company data into AI: what to do
Blanket bans rarely work; people switch to personal accounts. It works better to provide an approved route (enterprise plan or private deployment) plus data classification and auditing.
verified 2026-10-223 official sources
Scenario: Private LLMs and knowledge bases for the enterprise →
Symptoms
- Staff use personal accounts for customer data or code
- You are unsure which AI services train on inputs
Common causes
- There is no approved AI tool, so people use consumer versions
- Consumer and enterprise data terms differ
How to fix
- Classify data (public, internal, confidential, regulated) and state which AI may handle each level
- Provide an approved route: ChatGPT Enterprise / Gemini for Workspace / Claude enterprise plans (officially no training on business data by default), or a private Open WebUI / LibreChat with internal models
- Send every call through a gateway such as LiteLLM with central keys and audit logs (Langfuse)
- Detect sensitive data (IDs, phone numbers, secrets in code) at the gateway or endpoint
- Publish a one-page AI policy, train staff and review quarterly
Notes
- Vendor terms change; rely on the contract text when signing
- Regulated industries must also meet sector rules on data transfer and retention
Official references
Compiled from official documentation and public discussions on 2026-10-22; not yet reproduced in our own environment. Follow the official docs if they differ.